#include <InverseGamma.h>

Inheritance diagram for muq::Modeling::InverseGamma:

Detailed Description

Defines the inverse gamma distribution, which has probability density function

\[ \pi(x) = \frac{\beta^\alpha}{\Gamma(\alpha)}x^{-\alpha-1}\exp\left(-\frac{\beta}{x}\right), \]

where \(\alpha\) and \(\beta\) are parameters in the distribution. For multivariate \(x\), it is assumed that all components of \(x\) are independent. However, each component can have different parameters \(\alpha\) and \(\beta\).

Definition at line 17 of file InverseGamma.h.

Public Member Functions
	InverseGamma (double alphaIn, double betaIn)

	InverseGamma (Eigen::VectorXd const &alphaIn, Eigen::VectorXd const &betaIn)

virtual	~InverseGamma ()=default

Public Member Functions inherited from muq::Modeling::Distribution
	Distribution (unsigned int varSizeIn, Eigen::VectorXi const &hyperSizesIn=Eigen::VectorXi())

virtual	~Distribution ()=default

virtual double	LogDensity (ref_vector< Eigen::VectorXd > const &inputs)
	Evaluate the log-density. More...

virtual double	LogDensity (std::vector< Eigen::VectorXd > const &inputs)

	VARIADIC_TO_REFVECTOR (LogDensity, Eigen::VectorXd, double)

virtual Eigen::VectorXd	GradLogDensity (unsigned int wrt, std::vector< Eigen::VectorXd > const &inputs)

virtual Eigen::VectorXd	GradLogDensity (unsigned int wrt, ref_vector< Eigen::VectorXd > const &inputs)

template<typename... Args>
Eigen::VectorXd	GradLogDensity (unsigned int wrt, Args... args)

virtual Eigen::VectorXd	ApplyLogDensityHessian (unsigned int const inWrt1, unsigned int const inWrt2, ref_vector< Eigen::VectorXd > const &input, Eigen::VectorXd const &vec)

virtual Eigen::VectorXd	ApplyLogDensityHessian (unsigned int const inWrt1, unsigned int const inWrt2, std::vector< Eigen::VectorXd > const &input, Eigen::VectorXd const &vec)

Eigen::VectorXd	Sample (ref_vector< Eigen::VectorXd > const &inputs)
	Sample the distribution. More...

Eigen::VectorXd	Sample (std::vector< Eigen::VectorXd > const &inputs)

Eigen::VectorXd	Sample ()
	Sample the distribution with no inputs. More...

	VARIADIC_TO_REFVECTOR (Sample, Eigen::VectorXd, Eigen::VectorXd)

std::shared_ptr< Density >	AsDensity ()
	Returns a density built from this distribution. More...

std::shared_ptr< RandomVariable >	AsVariable ()
	Returns a random variable built from this distribution. More...

Public Attributes
const Eigen::VectorXd	alpha

const Eigen::VectorXd	beta

Public Attributes inherited from muq::Modeling::Distribution
const unsigned int	varSize

const Eigen::VectorXi	hyperSizes

Constructor & Destructor Documentation

◆ InverseGamma() [1/2]

InverseGamma::InverseGamma	(	double	alphaIn,
		double	betaIn
	)

Definition at line 15 of file InverseGamma.cpp.

◆ InverseGamma() [2/2]

InverseGamma::InverseGamma	(	Eigen::VectorXd const &	alphaIn,
		Eigen::VectorXd const &	betaIn
	)

Definition at line 8 of file InverseGamma.cpp.

◆ ~InverseGamma()

virtual muq::Modeling::InverseGamma::~InverseGamma ( )

virtualdefault

Member Function Documentation

◆ ComputeConstant()

double InverseGamma::ComputeConstant	(	Eigen::VectorXd const &	alphaIn,
		Eigen::VectorXd const &	betaIn
	)

staticprivate

Definition at line 19 of file InverseGamma.cpp.

References logConst.

◆ LogDensityImpl()

double InverseGamma::LogDensityImpl ( ref_vector< Eigen::VectorXd > const & inputs )

overrideprivatevirtual

Implement the log-density.

If known, the log-density should be implemented by a child. If it is not overridden then the default behavior is to return negative infinity (-1.0*std::numeric_limits<double>::infinity()).

Parameters

[in] inputs the vector of inputs to the log-density

Returns: The log density

Reimplemented from muq::Modeling::Distribution.

Definition at line 29 of file InverseGamma.cpp.

References alpha, beta, and logConst.

◆ SampleImpl()

Eigen::VectorXd InverseGamma::SampleImpl ( ref_vector< Eigen::VectorXd > const & inputs )

overrideprivatevirtual

Sample the distribution.

Reimplemented from muq::Modeling::Distribution.

Definition at line 40 of file InverseGamma.cpp.

References alpha, and beta.

Member Data Documentation

◆ alpha

const Eigen::VectorXd muq::Modeling::InverseGamma::alpha

Definition at line 30 of file InverseGamma.h.

Referenced by LogDensityImpl(), and SampleImpl().

◆ beta

const Eigen::VectorXd muq::Modeling::InverseGamma::beta

Definition at line 31 of file InverseGamma.h.

Referenced by LogDensityImpl(), and SampleImpl().

◆ logConst

const double muq::Modeling::InverseGamma::logConst

private

Definition at line 38 of file InverseGamma.h.

Referenced by ComputeConstant(), and LogDensityImpl().

The documentation for this class was generated from the following files:

doxygen_prep/MUQ/Modeling/Distributions/InverseGamma.h
doxygen_prep/modules/Modeling/src/Distributions/InverseGamma.cpp